mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-24 02:14:35 +00:00
ggml : add Q4_3 quantization (#1082)
This commit is contained in:
Georgi Gerganov
GitHub
parent
6a9661ea5a
commit
e0305ead3a
@ -15,6 +15,7 @@ int main(int argc, char ** argv) {
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fprintf(stderr, " type = %d - q4_0\n", LLAMA_FTYPE_MOSTLY_Q4_0);
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fprintf(stderr, " type = %d - q4_1\n", LLAMA_FTYPE_MOSTLY_Q4_1);
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fprintf(stderr, " type = %d - q4_2\n", LLAMA_FTYPE_MOSTLY_Q4_2);
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fprintf(stderr, " type = %d - q4_3\n", LLAMA_FTYPE_MOSTLY_Q4_3);
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return 1;
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}
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312
ggml.c
312
ggml.c
@ -637,7 +637,7 @@ typedef struct {
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float m; // min
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uint8_t qs[QK4_1 / 2]; // nibbles / quants
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} block_q4_1;
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static_assert(sizeof(block_q4_1) == sizeof(float) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
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static_assert(sizeof(block_q4_1) == 2 * sizeof(float) + QK4_1 / 2, "wrong q4_1 block size/padding");
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#define QK4_2 16
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typedef struct {
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@ -646,6 +646,14 @@ typedef struct {
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} block_q4_2;
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static_assert(sizeof(block_q4_2) == sizeof(ggml_fp16_t) + QK4_2 / 2, "wrong q4_2 block size/padding");
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#define QK4_3 16
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typedef struct {
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ggml_fp16_t d; // delta
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ggml_fp16_t m; // min
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uint8_t qs[QK4_3 / 2]; // nibbles / quants
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} block_q4_3;
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static_assert(sizeof(block_q4_3) == 2 * sizeof(ggml_fp16_t) + QK4_3 / 2, "wrong q4_3 block size/padding");
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#define QK8_0 32
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typedef struct {
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float d; // delta
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@ -1203,7 +1211,6 @@ static void quantize_row_q4_2_rmse(const float * restrict x, block_q4_2 * restri
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const int nb = k / QK4_2;
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for (int i = 0; i < nb; i++) {
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float scale = kquantize_q4_with_bounds(QK4_2, -8, 7, x, CANDIDATE_COUNT, candidates, L);
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y[i].d = GGML_FP32_TO_FP16(scale);
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@ -1231,6 +1238,49 @@ static void quantize_row_q4_2(const float * restrict x, void * restrict vy, int
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quantize_row_q4_2_rmse(x, y, k);
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}
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static void quantize_row_q4_3_reference(const float * restrict x, block_q4_3 * restrict y, int k) {
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assert(k % QK4_3 == 0);
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const int nb = k / QK4_3;
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for (int i = 0; i < nb; i++) {
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float min = FLT_MAX;
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float max = -FLT_MAX;
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for (int l = 0; l < QK4_3; l++) {
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const float v = x[i*QK4_3 + l];
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if (v < min) min = v;
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if (v > max) max = v;
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}
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const float d = (max - min) / ((1 << 4) - 1);
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const float id = d ? 1.0f/d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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y[i].m = GGML_FP32_TO_FP16(min);
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for (int l = 0; l < QK4_3; l += 2) {
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const float v0 = (x[i*QK4_3 + l + 0] - min)*id;
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const float v1 = (x[i*QK4_3 + l + 1] - min)*id;
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const uint8_t vi0 = (int) (v0 + 0.5f);
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const uint8_t vi1 = (int) (v1 + 0.5f);
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assert(vi0 < 16);
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assert(vi1 < 16);
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y[i].qs[l/2] = vi0 | (vi1 << 4);
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}
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}
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}
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static void quantize_row_q4_3(const float * restrict x, void * restrict vy, int k) {
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assert(k % QK4_3 == 0);
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block_q4_3 * restrict y = vy;
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quantize_row_q4_3_reference(x, y, k);
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}
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// reference implementation for deterministic creation of model files
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static void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict y, int k) {
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assert(k % QK8_0 == 0);
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@ -1635,9 +1685,40 @@ static void dequantize_row_q4_2(const void * restrict vx, float * restrict y, in
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}
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}
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static void dequantize_row_q4_3(const void * restrict vx, float * restrict y, int k) {
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assert(k % QK4_3 == 0);
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const int nb = k / QK4_3;
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const block_q4_3 * restrict x = vx;
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for (int i = 0; i < nb; i++) {
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const float d = GGML_FP16_TO_FP32(x[i].d);
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const float m = GGML_FP16_TO_FP32(x[i].m);
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const uint8_t * restrict pp = x[i].qs;
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for (int l = 0; l < QK4_3; l += 2) {
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const uint8_t vi = pp[l/2];
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const int8_t vi0 = vi & 0xf;
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const int8_t vi1 = vi >> 4;
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const float v0 = vi0*d + m;
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const float v1 = vi1*d + m;
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y[i*QK4_3 + l + 0] = v0;
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y[i*QK4_3 + l + 1] = v1;
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assert(!isnan(y[i*QK4_3 + l + 0]));
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assert(!isnan(y[i*QK4_3 + l + 1]));
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}
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}
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}
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static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_1_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy);
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static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = {
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[GGML_TYPE_Q4_0] = {
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@ -1661,6 +1742,13 @@ static const quantize_fns_t quantize_fns[GGML_TYPE_COUNT] = {
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_2_q8_0,
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},
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[GGML_TYPE_Q4_3] = {
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.dequantize_row_q = dequantize_row_q4_3,
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.quantize_row_q = quantize_row_q4_3,
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.quantize_row_q_reference = (quantize_row_q_t) quantize_row_q4_3_reference, // TODO: RMSE optimization
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.quantize_row_q_dot = quantize_row_q8_0,
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.vec_dot_q = ggml_vec_dot_q4_3_q8_0,
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},
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[GGML_TYPE_Q8_0] = {
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.dequantize_row_q = NULL, // TODO
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.quantize_row_q = quantize_row_q8_0,
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@ -2655,6 +2743,7 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
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const block_q4_2 * restrict x0_1 = &x[2*(i + 0) + 1];
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const block_q4_2 * restrict x1_0 = &x[2*(i + 1) + 0];
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const block_q4_2 * restrict x1_1 = &x[2*(i + 1) + 1];
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const block_q8_0 * restrict y0 = &y[i + 0];
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const block_q8_0 * restrict y1 = &y[i + 1];
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@ -2809,6 +2898,154 @@ static void ggml_vec_dot_q4_2_q8_0(const int n, float * restrict s, const void *
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*s = sumf;
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}
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static void ggml_vec_dot_q4_3_q8_0(const int n, float * restrict s, const void * restrict vx, const void * restrict vy) {
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const int nb = n / QK8_0;
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assert(n % QK8_0 == 0);
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assert(nb % 2 == 0);
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assert(QK8_0 == 2*QK4_2);
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const block_q4_3 * restrict x = vx;
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const block_q8_0 * restrict y = vy;
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float sumf = 0.0;
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#if defined(__ARM_NEON)
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float32x4_t sumv0 = vdupq_n_f32(0.0f);
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float32x4_t sumv1 = vdupq_n_f32(0.0f);
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for (int i = 0; i < nb; i += 2) {
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const block_q4_3 * restrict x0_0 = &x[2*(i + 0) + 0];
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const block_q4_3 * restrict x0_1 = &x[2*(i + 0) + 1];
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const block_q4_3 * restrict x1_0 = &x[2*(i + 1) + 0];
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const block_q4_3 * restrict x1_1 = &x[2*(i + 1) + 1];
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const block_q8_0 * restrict y0 = &y[i + 0];
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const block_q8_0 * restrict y1 = &y[i + 1];
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const uint8x16_t m4b = vdupq_n_u8(0xf);
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const float x0_0d = GGML_FP16_TO_FP32(x0_0->d);
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const float x0_1d = GGML_FP16_TO_FP32(x0_1->d);
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const float x1_0d = GGML_FP16_TO_FP32(x1_0->d);
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const float x1_1d = GGML_FP16_TO_FP32(x1_1->d);
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const float x0_0m = GGML_FP16_TO_FP32(x0_0->m);
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const float x0_1m = GGML_FP16_TO_FP32(x0_1->m);
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const float x1_0m = GGML_FP16_TO_FP32(x1_0->m);
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const float x1_1m = GGML_FP16_TO_FP32(x1_1->m);
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const uint8x16_t v0_0 = vcombine_u8(vld1_u8(x0_0->qs), vld1_u8(x0_1->qs));
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const uint8x16_t v0_1 = vcombine_u8(vld1_u8(x1_0->qs), vld1_u8(x1_1->qs));
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// 4-bit -> 8-bit
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const int8x16_t v0_0l = vreinterpretq_s8_u8(vandq_u8 (v0_0, m4b));
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const int8x16_t v0_0h = vreinterpretq_s8_u8(vshrq_n_u8(v0_0, 4));
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const int8x16_t v0_1l = vreinterpretq_s8_u8(vandq_u8 (v0_1, m4b));
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const int8x16_t v0_1h = vreinterpretq_s8_u8(vshrq_n_u8(v0_1, 4));
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// interleave
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const int8x16_t v0_0lz = vzip1q_s8(v0_0l, v0_0h);
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const int8x16_t v0_0hz = vzip2q_s8(v0_0l, v0_0h);
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const int8x16_t v0_1lz = vzip1q_s8(v0_1l, v0_1h);
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const int8x16_t v0_1hz = vzip2q_s8(v0_1l, v0_1h);
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// load y
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const int8x16_t v1_0l = vld1q_s8(y0->qs);
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const int8x16_t v1_0h = vld1q_s8(y0->qs + 16);
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const int8x16_t v1_1l = vld1q_s8(y1->qs);
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const int8x16_t v1_1h = vld1q_s8(y1->qs + 16);
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const int16x8_t sy0_0 = vaddq_s16(vmovl_s8(vget_low_s8(v1_0l)), vmovl_s8(vget_high_s8(v1_0l)));
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const int16x8_t sy0_1 = vaddq_s16(vmovl_s8(vget_low_s8(v1_0h)), vmovl_s8(vget_high_s8(v1_0h)));
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const int16x8_t sy1_0 = vaddq_s16(vmovl_s8(vget_low_s8(v1_1l)), vmovl_s8(vget_high_s8(v1_1l)));
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const int16x8_t sy1_1 = vaddq_s16(vmovl_s8(vget_low_s8(v1_1h)), vmovl_s8(vget_high_s8(v1_1h)));
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy0_0), vget_high_s16(sy0_0))), x0_0m*y0->d);
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy0_1), vget_high_s16(sy0_1))), x0_1m*y0->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy1_0), vget_high_s16(sy1_0))), x1_0m*y1->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddl_s16(vget_low_s16(sy1_1), vget_high_s16(sy1_1))), x1_1m*y1->d);
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#if defined(__ARM_FEATURE_DOTPROD)
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_0lz, v1_0l)), x0_0d*y0->d);
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_0hz, v1_0h)), x0_1d*y0->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_1lz, v1_1l)), x1_0d*y1->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vdotq_s32(vdupq_n_s32(0), v0_1hz, v1_1h)), x1_1d*y1->d);
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#else
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const int16x8_t pl0l = vmull_s8(vget_low_s8 (v0_0lz), vget_low_s8 (v1_0l));
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const int16x8_t pl0h = vmull_s8(vget_high_s8(v0_0lz), vget_high_s8(v1_0l));
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const int16x8_t ph0l = vmull_s8(vget_low_s8 (v0_0hz), vget_low_s8 (v1_0h));
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const int16x8_t ph0h = vmull_s8(vget_high_s8(v0_0hz), vget_high_s8(v1_0h));
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const int16x8_t pl1l = vmull_s8(vget_low_s8 (v0_1lz), vget_low_s8 (v1_1l));
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const int16x8_t pl1h = vmull_s8(vget_high_s8(v0_1lz), vget_high_s8(v1_1l));
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const int16x8_t ph1l = vmull_s8(vget_low_s8 (v0_1hz), vget_low_s8 (v1_1h));
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const int16x8_t ph1h = vmull_s8(vget_high_s8(v0_1hz), vget_high_s8(v1_1h));
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const int32x4_t pl0 = vaddq_s32(vpaddlq_s16(pl0l), vpaddlq_s16(pl0h));
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const int32x4_t ph0 = vaddq_s32(vpaddlq_s16(ph0l), vpaddlq_s16(ph0h));
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const int32x4_t pl1 = vaddq_s32(vpaddlq_s16(pl1l), vpaddlq_s16(pl1h));
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const int32x4_t ph1 = vaddq_s32(vpaddlq_s16(ph1l), vpaddlq_s16(ph1h));
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(pl0), x0_0d*y0->d);
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sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(ph0), x0_1d*y0->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(pl1), x1_0d*y1->d);
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sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(ph1), x1_1d*y1->d);
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#endif
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}
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sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
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#else
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// scalar
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for (int i = 0; i < nb; i++) {
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const uint8_t * restrict x0 = x[2*i + 0].qs;
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const uint8_t * restrict x1 = x[2*i + 1].qs;
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const int8_t * restrict y0 = y[i].qs;
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const float d0 = GGML_FP16_TO_FP32(x[2*i + 0].d);
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const float m0 = GGML_FP16_TO_FP32(x[2*i + 0].m);
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const float d1 = GGML_FP16_TO_FP32(x[2*i + 1].d);
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const float m1 = GGML_FP16_TO_FP32(x[2*i + 1].m);
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int sy_0 = 0;
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int sy_1 = 0;
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int sxy_0 = 0;
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int sxy_1 = 0;
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for (int j = 0; j < QK8_0/4; j++) {
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const uint8_t v0 = x0[j];
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const uint8_t v1 = x1[j];
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const int x0_0 = v0 & 0xf;
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const int x1_0 = v0 >> 4;
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const int x0_1 = v1 & 0xf;
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const int x1_1 = v1 >> 4;
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const int y0_0 = y0[2*j + 0];
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const int y1_0 = y0[2*j + 1];
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const int y0_1 = y0[2*(j + QK8_0/4) + 0];
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const int y1_1 = y0[2*(j + QK8_0/4) + 1];
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sy_0 += y0_0 + y1_0;
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sy_1 += y0_1 + y1_1;
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sxy_0 += x0_0*y0_0 + x1_0*y1_0;
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sxy_1 += x0_1*y0_1 + x1_1*y1_1;
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}
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sumf += (d0*sxy_0 + m0*sy_0)*y[i].d;
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sumf += (d1*sxy_1 + m1*sy_1)*y[i].d;
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}
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#endif
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*s = sumf;
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}
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// compute GGML_VEC_DOT_UNROLL dot products at once
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// xs - x row stride in bytes
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inline static void ggml_vec_dot_f16_unroll(const int n, const int xs, float * restrict s, void * restrict xv, ggml_fp16_t * restrict y) {
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@ -3056,12 +3293,13 @@ static const int GGML_BLCK_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_0] = QK4_0,
|
||||
[GGML_TYPE_Q4_1] = QK4_1,
|
||||
[GGML_TYPE_Q4_2] = QK4_2,
|
||||
[GGML_TYPE_Q4_3] = QK4_3,
|
||||
[GGML_TYPE_Q8_0] = QK8_0,
|
||||
[GGML_TYPE_I8] = 1,
|
||||
[GGML_TYPE_I16] = 1,
|
||||
[GGML_TYPE_I32] = 1,
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 9, "GGML_BLCK_SIZE is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_BLCK_SIZE is outdated");
|
||||
|
||||
static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_F32] = sizeof(float),
|
||||
@ -3069,12 +3307,13 @@ static const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_0] = sizeof(block_q4_0),
|
||||
[GGML_TYPE_Q4_1] = sizeof(block_q4_1),
|
||||
[GGML_TYPE_Q4_2] = sizeof(block_q4_2),
|
||||
[GGML_TYPE_Q4_3] = sizeof(block_q4_3),
|
||||
[GGML_TYPE_Q8_0] = sizeof(block_q8_0),
|
||||
[GGML_TYPE_I8] = sizeof(int8_t),
|
||||
[GGML_TYPE_I16] = sizeof(int16_t),
|
||||
[GGML_TYPE_I32] = sizeof(int32_t),
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 9, "GGML_TYPE_SIZE is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_TYPE_SIZE is outdated");
|
||||
|
||||
|
||||
static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = {
|
||||
@ -3083,12 +3322,13 @@ static const char * GGML_TYPE_NAME[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_0] = "q4_0",
|
||||
[GGML_TYPE_Q4_1] = "q4_1",
|
||||
[GGML_TYPE_Q4_2] = "q4_2",
|
||||
[GGML_TYPE_Q4_3] = "q4_3",
|
||||
[GGML_TYPE_Q8_0] = "q8_0",
|
||||
[GGML_TYPE_I8] = "i8",
|
||||
[GGML_TYPE_I16] = "i16",
|
||||
[GGML_TYPE_I32] = "i32",
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 9, "GGML_TYPE_NAME is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_TYPE_NAME is outdated");
|
||||
|
||||
static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_F32] = false,
|
||||
@ -3096,12 +3336,13 @@ static bool GGML_IS_QUANTIZED[GGML_TYPE_COUNT] = {
|
||||
[GGML_TYPE_Q4_0] = true,
|
||||
[GGML_TYPE_Q4_1] = true,
|
||||
[GGML_TYPE_Q4_2] = true,
|
||||
[GGML_TYPE_Q4_3] = true,
|
||||
[GGML_TYPE_Q8_0] = true,
|
||||
[GGML_TYPE_I8] = false,
|
||||
[GGML_TYPE_I16] = false,
|
||||
[GGML_TYPE_I32] = false,
|
||||
};
|
||||
static_assert(GGML_TYPE_COUNT == 9, "GGML_IS_QUANTIZED is outdated");
|
||||
static_assert(GGML_TYPE_COUNT == 10, "GGML_IS_QUANTIZED is outdated");
|
||||
|
||||
static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
|
||||
"NONE",
|
||||
@ -3363,7 +3604,7 @@ static inline bool ggml_can_mul_mat(const struct ggml_tensor * t0, const struct
|
||||
(t0->ne[3] == t1->ne[3]);
|
||||
}
|
||||
|
||||
static inline bool ggml_is_quantized(enum ggml_type type) {
|
||||
bool ggml_is_quantized(enum ggml_type type) {
|
||||
return GGML_IS_QUANTIZED[type];
|
||||
}
|
||||
|
||||
@ -6313,6 +6554,7 @@ static void ggml_compute_forward_add(
|
||||
case GGML_TYPE_Q4_0:
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
{
|
||||
ggml_compute_forward_add_q_f32(params, src0, src1, dst);
|
||||
} break;
|
||||
@ -7798,6 +8040,9 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
else if (type == GGML_TYPE_Q4_2) {
|
||||
dequantize_row_q_cuda = dequantize_row_q4_2_cuda;
|
||||
}
|
||||
else if (type == GGML_TYPE_Q4_3) {
|
||||
dequantize_row_q_cuda = dequantize_row_q4_3_cuda;
|
||||
}
|
||||
else {
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
@ -7952,6 +8197,7 @@ static void ggml_compute_forward_mul_mat(
|
||||
case GGML_TYPE_Q4_0:
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
{
|
||||
ggml_compute_forward_mul_mat_q_f32(params, src0, src1, dst);
|
||||
@ -7969,34 +8215,6 @@ static void ggml_compute_forward_mul_mat(
|
||||
GGML_ASSERT(false);
|
||||
} break;
|
||||
}
|
||||
|
||||
#if 0
|
||||
if (src0->type == GGML_TYPE_F16 || src0->type == GGML_TYPE_Q4_1) {
|
||||
static int first = 8;
|
||||
printf("src0: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", src0->ne[0], src0->ne[1], src0->ne[2]);
|
||||
printf("src1: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", src1->ne[0], src1->ne[1], src1->ne[2]);
|
||||
printf("dst: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", dst->ne[0], dst->ne[1], dst->ne[2]);
|
||||
if (first) {
|
||||
--first;
|
||||
} else {
|
||||
for (int k = 0; k < dst->ne[1]; ++k) {
|
||||
for (int j = 0; j < dst->ne[0]/16; ++j) {
|
||||
for (int i = 0; i < 16; ++i) {
|
||||
printf("%8.4f ", ((float *) dst->data)[k*dst->ne[0] + j*16 + i]);
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
printf("\n");
|
||||
}
|
||||
printf("\n");
|
||||
exit(0);
|
||||
}
|
||||
} else {
|
||||
printf("aaaa src0: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", src0->ne[0], src0->ne[1], src0->ne[2]);
|
||||
printf("aaaa src1: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", src1->ne[0], src1->ne[1], src1->ne[2]);
|
||||
printf("aaaa dst: ne0 = %5d, ne1 = %5d, ne2 = %5d\n", dst->ne[0], dst->ne[1], dst->ne[2]);
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
// ggml_compute_forward_scale
|
||||
@ -8208,6 +8426,7 @@ static void ggml_compute_forward_get_rows(
|
||||
case GGML_TYPE_Q4_0:
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
case GGML_TYPE_Q8_0:
|
||||
{
|
||||
ggml_compute_forward_get_rows_q(params, src0, src1, dst);
|
||||
@ -11947,6 +12166,29 @@ size_t ggml_quantize_q4_2(const float * src, void * dst, int n, int k, int64_t *
|
||||
return (n/QK4_2*sizeof(block_q4_2));
|
||||
}
|
||||
|
||||
size_t ggml_quantize_q4_3(const float * src, void * dst, int n, int k, int64_t * hist) {
|
||||
assert(k % QK4_3 == 0);
|
||||
const int nb = k / QK4_3;
|
||||
|
||||
for (int j = 0; j < n; j += k) {
|
||||
block_q4_3 * restrict y = (block_q4_3 *)dst + j/QK4_3;
|
||||
|
||||
quantize_row_q4_3_reference(src + j, y, k);
|
||||
|
||||
for (int i = 0; i < nb; i++) {
|
||||
for (int l = 0; l < QK4_3; l += 2) {
|
||||
const uint8_t vi0 = y[i].qs[l/2] & 0xF;
|
||||
const uint8_t vi1 = y[i].qs[l/2] >> 4;
|
||||
|
||||
hist[vi0]++;
|
||||
hist[vi1]++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return (n/QK4_3*sizeof(block_q4_3));
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
int ggml_cpu_has_avx(void) {
|
||||
|
||||
6
ggml.h
6
ggml.h
@ -205,7 +205,8 @@ enum ggml_type {
|
||||
GGML_TYPE_Q4_0 = 2,
|
||||
GGML_TYPE_Q4_1 = 3,
|
||||
GGML_TYPE_Q4_2 = 4,
|
||||
GGML_TYPE_Q8_0 = 5,
|
||||
GGML_TYPE_Q4_3 = 5,
|
||||
GGML_TYPE_Q8_0 = 6,
|
||||
GGML_TYPE_I8,
|
||||
GGML_TYPE_I16,
|
||||
GGML_TYPE_I32,
|
||||
@ -360,6 +361,8 @@ const char * ggml_type_name(enum ggml_type type);
|
||||
|
||||
size_t ggml_element_size(const struct ggml_tensor * tensor);
|
||||
|
||||
bool ggml_is_quantized(enum ggml_type type);
|
||||
|
||||
struct ggml_context * ggml_init(struct ggml_init_params params);
|
||||
void ggml_free(struct ggml_context * ctx);
|
||||
|
||||
@ -808,6 +811,7 @@ enum ggml_opt_result ggml_opt(
|
||||
size_t ggml_quantize_q4_0(const float * src, void * dst, int n, int k, int64_t * hist);
|
||||
size_t ggml_quantize_q4_1(const float * src, void * dst, int n, int k, int64_t * hist);
|
||||
size_t ggml_quantize_q4_2(const float * src, void * dst, int n, int k, int64_t * hist);
|
||||
size_t ggml_quantize_q4_3(const float * src, void * dst, int n, int k, int64_t * hist);
|
||||
|
||||
//
|
||||
// system info
|
||||
|
||||
10
llama.cpp
10
llama.cpp
@ -479,6 +479,7 @@ struct llama_file_loader {
|
||||
case GGML_TYPE_Q4_0:
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
break;
|
||||
default: {
|
||||
throw format("unrecognized tensor type %u\n", shard.type);
|
||||
@ -552,6 +553,7 @@ struct llama_file_saver {
|
||||
case GGML_TYPE_Q4_0:
|
||||
case GGML_TYPE_Q4_1:
|
||||
case GGML_TYPE_Q4_2:
|
||||
case GGML_TYPE_Q4_3:
|
||||
break;
|
||||
default: LLAMA_ASSERT(false);
|
||||
}
|
||||
@ -841,6 +843,7 @@ static const char *llama_ftype_name(enum llama_ftype ftype) {
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16:
|
||||
return "mostly Q4_1, some F16";
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_2: return "mostly Q4_2";
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_3: return "mostly Q4_3";
|
||||
default: return "unknown, may not work";
|
||||
}
|
||||
}
|
||||
@ -1575,6 +1578,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_0: quantized_type = GGML_TYPE_Q4_0; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_1: quantized_type = GGML_TYPE_Q4_1; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_2: quantized_type = GGML_TYPE_Q4_2; break;
|
||||
case LLAMA_FTYPE_MOSTLY_Q4_3: quantized_type = GGML_TYPE_Q4_3; break;
|
||||
default: throw format("invalid output file type %d\n", ftype);
|
||||
};
|
||||
|
||||
@ -1652,6 +1656,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
|
||||
{
|
||||
new_size = ggml_quantize_q4_2(f32_data, new_data, nelements, (int) tensor.ne.at(0), hist_cur.data());
|
||||
} break;
|
||||
case GGML_TYPE_Q4_3:
|
||||
{
|
||||
new_size = ggml_quantize_q4_3(f32_data, new_data, nelements, (int) tensor.ne.at(0), hist_cur.data());
|
||||
} break;
|
||||
default:
|
||||
LLAMA_ASSERT(false);
|
||||
}
|
||||
@ -1963,7 +1971,7 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
|
||||
base_t = dest_t;
|
||||
}
|
||||
|
||||
if (base_t->type == GGML_TYPE_Q4_0 || base_t->type == GGML_TYPE_Q4_1 || base_t->type == GGML_TYPE_Q4_2) {
|
||||
if (ggml_is_quantized(base_t->type)) {
|
||||
if (!warned) {
|
||||
fprintf(stderr, "%s: warning: using a lora adapter with a quantized model may result in poor quality, "
|
||||
"use a f16 or f32 base model with --lora-base\n", __func__);
|
||||
|
||||
1
llama.h
1
llama.h
@ -73,6 +73,7 @@ extern "C" {
|
||||
LLAMA_FTYPE_MOSTLY_Q4_1 = 3, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16 = 4, // tok_embeddings.weight and output.weight are F16
|
||||
LLAMA_FTYPE_MOSTLY_Q4_2 = 5, // except 1d tensors
|
||||
LLAMA_FTYPE_MOSTLY_Q4_3 = 6, // except 1d tensors
|
||||
};
|
||||
|
||||
LLAMA_API struct llama_context_params llama_context_default_params();
|
||||
|
||||
Loading…
Reference in New Issue
Block a user